World Bank Blogshttp://blogs.worldbank.org/planet.xml
IBRD and IDA: Working for a World Free of Poverty.enChart: Why Are Women Restricted From Working?http://blogs.worldbank.org/opendata/chart-why-are-women-restricted-working
<p>
<iframe allowtransparency="true" frameborder="0" height="380" id="datawrapper-chart-r2A2a" scrolling="no" src="//datawrapper.dwcdn.net/r2A2a/4/" style="width: 0; min-width: 100% !important;"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["r2A2a"]={},window.datawrapper["r2A2a"].embedDeltas={"100":618,"200":482,"300":424,"400":424,"500":397,"700":380,"800":380,"900":380,"1000":380},window.datawrapper["r2A2a"].iframe=document.getElementById("datawrapper-chart-r2A2a"),window.datawrapper["r2A2a"].iframe.style.height=window.datawrapper["r2A2a"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["r2A2a"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("r2A2a"==b)window.datawrapper["r2A2a"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script></p>
<p>
Economies grow faster when more women work, but in every region of the world, restrictions exist on women’s employment. <a href="http://wbl.worldbank.org/">The 2018 edition of Women Business and the Law</a> examines 189 economies and finds that in 104 of them, women face some kind of restriction. 30% of economies restrict women from working in jobs deemed hazardous, arduous or morally inappropriate; 40% restrict women from working in certain industries, and 15% restrict women from working at night.</p>
<p>
&nbsp;</p>
<!--break-->Thu, 29 Mar 2018 10:00:00 -0400Tariq KhokharChart: Economic Development and the Composition of Wealthhttp://blogs.worldbank.org/opendata/chart-economic-development-and-composition-wealth
<p>
<iframe id="datawrapper-chart-juRem" src="//datawrapper.dwcdn.net/juRem/3/" scrolling="no" frameborder="0" allowtransparency="true" style="width: 0; min-width: 100% !important;" height="337"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["juRem"]={},window.datawrapper["juRem"].embedDeltas={"100":496,"200":435,"300":364,"400":364,"500":364,"700":337,"800":337,"900":337,"1000":337},window.datawrapper["juRem"].iframe=document.getElementById("datawrapper-chart-juRem"),window.datawrapper["juRem"].iframe.style.height=window.datawrapper["juRem"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["juRem"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("juRem"==b)window.datawrapper["juRem"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script></p>
<p>
The composition of wealth fundamentally changes with economic development. Natural capital—energy, minerals, land and forests—is the largest component of wealth in low-income countries. Its value goes up, but its share of total wealth decreases as economies develop. By contrast, the share of human capital, estimated as the present value of future incomes for the labor force, increases as economies develop. Overall, human capital accounts for two-thirds of the wealth of nations.&nbsp;Read more in&nbsp;<a href="https://openknowledge.worldbank.org/handle/10986/29001">The Changing Wealth of Nations</a></p>
<p>
&nbsp;</p>
<!--break-->Tue, 30 Jan 2018 16:00:00 -0500Tariq KhokharChart: Global Wealth Grew 66% Between 1995 and 2014http://blogs.worldbank.org/opendata/chart-global-wealth-grew-66-between-1995-and-2014
<p>
<iframe id="datawrapper-chart-UBfxA" src="//datawrapper.dwcdn.net/UBfxA/1/" scrolling="no" frameborder="0" allowtransparency="true" style="width: 0; min-width: 100% !important;" height="450"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["UBfxA"]={},window.datawrapper["UBfxA"].embedDeltas={"100":619,"200":521,"300":477,"400":477,"500":450,"700":450,"800":450,"900":450,"1000":450},window.datawrapper["UBfxA"].iframe=document.getElementById("datawrapper-chart-UBfxA"),window.datawrapper["UBfxA"].iframe.style.height=window.datawrapper["UBfxA"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["UBfxA"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("UBfxA"==b)window.datawrapper["UBfxA"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script></p>
<p>
Global wealth grew by 66% between 1995 and 2014 to a total of over 1,140 Trillion dollars. The share of the world’s wealth held by middle-income countries is growing — it increased from 19% to 28% between 1995 and 2014, while the share of high-income OECD countries fell from 75% to 65%. Read more in&nbsp;<a href="https://openknowledge.worldbank.org/handle/10986/29001">The Changing Wealth of Nations</a></p>
<p>
&nbsp;</p>
<!--break-->Tue, 30 Jan 2018 16:00:00 -0500Tariq KhokharData science competition: predicting poverty is hard - can you do it better? http://blogs.worldbank.org/opendata/data-science-competition-predicting-poverty-hard-can-you-do-it-better
<div style="text-align:center">
<img alt="" height="676" src="https://blogs.worldbank.org/opendata/files/opendata/screen_shot_2018-01-08_at_9.16.51_am.png" title="" width="1138" /></div>
&nbsp;
<p>
If you want to reduce poverty, you have to be able to identify the poor. But <a href="http://www.worldbank.org/en/topic/measuringpoverty">measuring poverty is difficult and expensive</a>, as it requires the collection of detailed data on household consumption or income. We just <a href="https://www.drivendata.org/competitions/50/worldbank-poverty-prediction/">launched a competition</a> together with data science platform <a href="https://www.drivendata.org/">Driven Data</a>, to help us see how well we can predict a household’s poverty status based on easy-to-collect information and using machine learning algorithms.</p>
<p>
The competition supplies a set of training data with anonymized qualitative variables from household surveys in 3 countries, including the “poor” or “not poor” classification for each observation.</p>
<p>
The challenge is to build models which can accurately classify households from a different set of test data (with the poor/not poor classification removed!) for the same 3 countries, and then submit them for scoring. Performance is measured by the <a href="https://en.wikipedia.org/wiki/Loss_functions_for_classification">mean log loss</a> for the 3 countries which tells us how accurate the classification models developed are.</p>
<p>
Prizes are $6,000; $4,000; and $2,500 for the top 3 performing entries, plus a $2,500 bonus prize for the top-performing entry from a low- or lower-middle income country. The deadline for entries is February 28th 2018.</p>
<p>
You can read the <a href="https://www.drivendata.org/competitions/50/worldbank-poverty-prediction/page/99/">full problem description and enter the competition here</a>, and see the Driven Data team’s <a href="http://drivendata.co/blog/worldbank-poverty-benchmark/">“benchmark solution”</a> based on a random forest classifier.</p>
<p>
Good luck - we look forward to seeing your solutions!</p>
<!--break-->Mon, 08 Jan 2018 10:30:00 -0500Tariq KhokharChart: 100 Million People Pushed into Poverty by Health Costs in 2010 http://blogs.worldbank.org/opendata/chart-100-million-people-pushed-poverty-health-costs-2010
<p>
<iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="490" id="datawrapper-chart-C3fgS" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//datawrapper.dwcdn.net/C3fgS/1/" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><br />
<br />
<script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["C3fgS"]={},window.datawrapper["C3fgS"].embedDeltas={"100":800,"200":619,"300":576,"400":533,"500":533,"600":533,"700":490,"800":490,"900":490,"1000":490},window.datawrapper["C3fgS"].iframe=document.getElementById("datawrapper-chart-C3fgS"),window.datawrapper["C3fgS"].iframe.style.height=window.datawrapper["C3fgS"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["C3fgS"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("C3fgS"==b)window.datawrapper["C3fgS"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script></p>
<p>
Universal health coverage (UHC) means that all people can obtain the health services they need without suffering financial hardship. A <a href="http://documents.worldbank.org/curated/en/640121513095868125/Tracking-universal-health-coverage-2017-global-monitoring-report">new report produced by the World Bank and the World Health Organization</a>, finds that health expenditures are pushing about 100 million people per year into “extreme poverty,” those who live on $1.90 or less a day; and about 180 million per year into poverty using a $3.10 per day threshold. </p>
<p>You can access the report, data, interactive visualizations, and background papers at: <a href="http://data.worldbank.org/universal-health-coverage/ ">http://data.worldbank.org/universal-health-coverage/</a>
</p>
<!--break-->Wed, 13 Dec 2017 12:00:00 -0500Tariq KhokharChart: 16 of the 17 Warmest Years on Record Occurred Since 2001http://blogs.worldbank.org/opendata/chart-16-17-warmest-years-record-occurred-2001
<iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="448" id="datawrapper-chart-j7I0u" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//datawrapper.dwcdn.net/j7I0u/1/" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["j7I0u"]={},window.datawrapper["j7I0u"].embedDeltas={"100":715,"200":560,"300":517,"400":491,"500":474,"600":448,"700":448,"800":448,"900":448,"1000":448},window.datawrapper["j7I0u"].iframe=document.getElementById("datawrapper-chart-j7I0u"),window.datawrapper["j7I0u"].iframe.style.height=window.datawrapper["j7I0u"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["j7I0u"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("j7I0u"==b)window.datawrapper["j7I0u"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script>
<p>
Sixteen of the 17 warmest years in the 136-year record have occurred since 2001. The year 2016 ranks as the warmest on record. Recent analysis finds that climate change could push more than 100 million more people into poverty by 2030. But good development—­rapid, inclusive, and climate informed—­can prevent most of the impacts of climate change on extreme poverty by 2030.</p>
<p>
&nbsp;</p>
<!--break-->Mon, 04 Dec 2017 11:00:00 -0500Tariq KhokharChart: CO2 Emissions are Unprecedentedhttp://blogs.worldbank.org/opendata/chart-co2-emissions-are-unprecedented
<iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="487" id="datawrapper-chart-bdOSa" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//datawrapper.dwcdn.net/bdOSa/1/" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["bdOSa"]={},window.datawrapper["bdOSa"].embedDeltas={"100":616,"200":530,"300":530,"400":487,"500":487,"600":487,"700":487,"800":487,"900":487,"1000":487},window.datawrapper["bdOSa"].iframe=document.getElementById("datawrapper-chart-bdOSa"),window.datawrapper["bdOSa"].iframe.style.height=window.datawrapper["bdOSa"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["bdOSa"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("bdOSa"==b)window.datawrapper["bdOSa"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script>
<p>
Global emissions of carbon dioxide, a major greenhouse gas and driver of climate change, increased from 22.4 billion metric tons in 1990 to 35.8 billion in 2013, a rise of 60 percent. The increase in emissions of CO2 and other greenhouse gases has contributed to a rise of about 0.8 degrees Celsius in the mean global temperature above pre-industrial times. Read more in the <a href="http://data.worldbank.org/sdgatlas">2017 Atlas of Sustainable Development Goals</a><br />
&nbsp;</p>
<!--break-->Mon, 04 Dec 2017 11:00:00 -0500Tariq KhokharChart: It's Never Been Faster to Start A Businesshttp://blogs.worldbank.org/opendata/chart-its-never-been-faster-start-business
<iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="415" id="datawrapper-chart-yXmDW" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//datawrapper.dwcdn.net/yXmDW/4/" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["yXmDW"]={},window.datawrapper["yXmDW"].embedDeltas={"100":566,"200":482,"300":440,"400":440,"500":415,"600":415,"700":415,"800":415,"900":415,"1000":415},window.datawrapper["yXmDW"].iframe=document.getElementById("datawrapper-chart-yXmDW"),window.datawrapper["yXmDW"].iframe.style.height=window.datawrapper["yXmDW"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["yXmDW"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("yXmDW"==b)window.datawrapper["yXmDW"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script>
<p>
Over the last 15 years, the Doing Business project has recorded nearly 3,200 reforms in 186 economies around the world. The area that's seen the greatest number of reforms is starting a business. Today, the time taken to start a new small or medium business has less than halved to an average of 20 days worldwide, compared with 52 in 2003. Read more in <a href="http://www.doingbusiness.org/">Doing Business 2018</a></p>
<!--break-->Tue, 31 Oct 2017 10:15:00 -0400Tariq KhokharWhere does Chinese development finance go?http://blogs.worldbank.org/opendata/where-does-chinese-development-finance-go
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<p>
<em>This post looks at the recently updated <a href="http://aiddata.org/china">“Global Chinese Official Finance Dataset”</a> from research group AidData. The post is&nbsp;<a href="http://tariqkhokhar.com/data/aiddata-china-blog.html">also available here</a> as an <a href="http://rmarkdown.rstudio.com/r_notebooks.html">R Notebook</a> which means you see the code behind the charts and analysis.</em></p>
<div style="text-align:center">
<figure class="image" style="display:inline-block">
<img alt="Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank" height="400" src="http://farm8.staticflickr.com/7052/6892083827_82f060022d_b_d.jpg" title="" width="600" />
<figcaption>
<em>Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank</em></figcaption>
</figure>
</div>
<p>
China has provided foreign assistance to countries around the world since the 1950s. Since it’s not part of the <a href="http://www.oecd.org/development/developmentassistancecommitteedac.htm">DAC group of donors</a> who report their activities in a <a href="https://stats.oecd.org/Index.aspx?DataSetCode=CRS1">standard manner</a>, there isn’t an official dataset which breaks down where Chinese foreign assistance goes, and what it’s used for.</p>
<p>
A team of researchers at <a href="http://aiddata.org/#">AidData</a>, in the <a href="http://www.wm.edu/">College of William and Mary</a> have just updated their <a href="http://aiddata.org/data/chinese-global-official-finance-dataset">“Chinese Global Official Finance”</a> dataset. This is an unofficial compilation of over 4,000 Chinese-financed projects in 138 countries, from 2000 to 2014, based on a triangulation of public data from government systems, public records and media reports. The team have coded these projects with over 50 variables which help to group and characterize them.</p>
<div class="section level4" id="activity-level-data-on-an-increasingly-important-donor">
<h4>
Activity-level data on an increasingly important donor</h4>
<p>
This dataset is interesting for two reasons. First, China and other emerging donors are making an impact on the development finance landscape. As the Bank has reported in the past (see <a href="https://openknowledge.worldbank.org/bitstream/handle/10986/23328/9781464806810.pdf?sequence=1&amp;isAllowed=y">International Debt Statistics 2016</a>), bilateral creditors are a more important source of finance than they were just five years ago. And the majority of these increases are coming from emerging donors with China playing a prominent role.</p>
<p>
Second, this dataset’s activity-level data gives us a look at trends and allocations in Chinese bilateral finance which can inform further analysis and research. Organizations like the World Bank collect data on financial flows directly from government sources for our operational purposes, but we’re unable to make these detailed data publicly available. We compile these data into aggregate financial flow statistics presented from the “debtor perspective”, but they’re not disaggregated by individual counterparties or at an activity-level. So there can be value added from sources such as AidData’s China dataset.</p>
</div>
<div class="section level4" id="a-detailed-view-but-only-part-of-the-picture-of-all-financial-flows">
<h4>
A detailed view, but only part of the picture of all financial flows</h4>
<p>
However, this dataset has limitations. It only presents estimates of “official bilateral credits”. These are flows between two governments, and are just one part of the total financial flows coming from China. By contrast, the World Bank is able to integrate the granular data it collects from countries into the <a href="http://datatopics.worldbank.org/debt/ids/country/CHN">full set of financial flows</a> to and from its borrowing countries. This situates official bilateral credit among the broader spectrum of providers of long-term financing (such as bondholders, financial intermediaries, and other private sector entities), sources of short-term debt (including movements in bank deposits), and equity investments (foreign direct and portfolio investments). This data integration leads to better quality statistics.</p>
<p>
In short, AidData’s China dataset provides more detail on one type of financial flow, but is likely to be less reliable for a number of low-income countries. With these caveats in mind, I’ve done a quick exploration of the dataset to produce some summary statistics and give you an idea of what’s inside.&nbsp;</p>
</div>
<div class="section level4" id="looking-at-foreign-assistance-by-type-of-flow">
<h4>
Looking at foreign assistance by type of flow</h4>
<p>
First, let’s see what the trends in different types of foreign assistance look like. AidData researchers code the projects they’ve identified into three types of “flow”:</p>
<ol style="list-style-type: decimal">
<li>
<strong>Official Development Assistance (ODA)</strong>, which contains a grant element of 25% or more and is primarily intended for development.</li>
<li>
<strong>Other Official Flows (OOF)</strong>, where the grant element is under 25% and the the financing more commercial in nature.</li>
<li>
<strong>Vague Official Finance</strong>, where there isn’t enough information to assign it to either category.</li>
</ol>
<p>
Here are the total financial values of the projects in AidData’s dataset, grouped by flow type and year:</p>
<p>
<img alt="" src="http://tariqkhokhar.com/data/aiddata-china-blog_files/figure-html/unnamed-chunk-1-1.png" style="display: block; margin: auto;" title="" width="1350" /></p>
<p>
It looks like more Chinese finance is classed as OOF ($216bn in the period above) than ODA ($81bn), and that 2009 is a bit of an outlier. With this dataset, we next can figure out which countries are the top recipients of ODA and OOF, and also which sectors are most financed.</p>
<!--break-->
<p>
But first, let’s take advantage of the activity-level breakdown to see what accounts for the spike in 2009. At a guess, it’s going to be some large individual projects coded that year, so let’s look for OOF activities in 2009 which were &gt; $10bn:</p>
<table class="table table-striped table-hover" style="margin-left: auto; margin-right: auto;">
<caption>
OOF Projects in 2009 &gt; $10bn</caption>
<thead>
<tr>
<th style="text-align:right;">
ID</th>
<th style="text-align:left;">
Title/Description</th>
<th style="text-align:right;">
Amount</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:right;">
43012</td>
<td style="text-align:left;">
China Development Bank to offer loans totaling 25 billion USD in to Russian Roseneft and Transneft (linked to project #43069)</td>
<td style="text-align:right;">
13.6</td>
</tr>
<tr>
<td style="text-align:right;">
43069</td>
<td style="text-align:left;">
Roseneft takes out loan of 10 billion USD out of available 15 from China Development Bank (linked to #43012)</td>
<td style="text-align:right;">
20.4</td>
</tr>
</tbody>
</table>
<p>
<br />
It looks like part of the jump can be explained by two large projects involving Russian energy firms Transneft and Roseneft - they’re also referenced in this 2009 Reuters article about <a href="http://uk.reuters.com/article/uk-russia-china-oil-sb/china-lends-russia-25-billion-to-get-20-years-of-oil-idUKTRE51G3S620090217">China loaning Russia $25 billion to access to 20 years of oil.</a></p>
</div>
<div class="section level4" id="who-are-the-top-recipients-of-chinese-oda-and-oof">
<h4>
Who are the top recipients of Chinese ODA and OOF?</h4>
<p>
Switching back to an aggregate view - which countries have received the most ODA and OOF in the 15 years the dataset covers? We can aggregate total project values by flow type and look at the top 10 countries for each type of flow:</p>
<p>
<img alt="" src="http://tariqkhokhar.com/data/aiddata-china-blog_files/figure-html/unnamed-chunk-3-1.png" style="display: block; margin: auto;" title="" /><img alt="" src="http://tariqkhokhar.com/data/aiddata-china-blog_files/figure-html/unnamed-chunk-3-2.png" style="display: block; margin: auto;" title="" /><br />
This again shows the relative difference in size of ODA vs OOF but also has me asking some more questions - what are the Chinese ODA flows to Cuba? When we list them out, it looks like the majority of the $6.7bn figure above is debt forgiveness recorded in 2011.</p>
<table>
<caption>
ODA Projects Cuba 2000-2014</caption>
<thead>
<tr class="header">
<th align="right">
ID</th>
<th align="left">
Title/Description</th>
<th align="right">
Year</th>
<th align="right">
Amount</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="right">
36186</td>
<td align="left">
China reschedules $7.2 million Cuban debt</td>
<td align="right">
2008</td>
<td align="right">
9.9</td>
</tr>
<tr class="even">
<td align="right">
36187</td>
<td align="left">
China donates cash and materials for Cuban hurricane relief</td>
<td align="right">
2008</td>
<td align="right">
11.0</td>
</tr>
<tr class="odd">
<td align="right">
39195</td>
<td align="left">
China forgives US$ 6 billion worth of Cuban Debt</td>
<td align="right">
2011</td>
<td align="right">
6659.9</td>
</tr>
<tr class="even">
<td align="right">
39776</td>
<td align="left">
China donates 400,000 USD for Hurricane Sandy Relief</td>
<td align="right">
2012</td>
<td align="right">
0.4</td>
</tr>
</tbody>
</table>
</div>
<div class="section level4" id="which-sectors-receive-the-most-investment-via-oda-or-oof">
<h4>
Which sectors receive the most investment via ODA or OOF?</h4>
<p>
Finally, let’s take a look by sector. The AidData team have coded projects using <a href="http://www.oecd.org/dac/stats/purposecodessectorclassification.htm">DAC Sector Codes</a> and we can look at the relative allocation of resources across these by flow type:</p>
<p>
<img alt="" src="http://tariqkhokhar.com/data/aiddata-china-blog_files/figure-html/unnamed-chunk-5-1.png" style="display: block; margin: auto;" title="" /><img alt="" src="http://tariqkhokhar.com/data/aiddata-china-blog_files/figure-html/unnamed-chunk-5-2.png" style="display: block; margin: auto;" title="" /></p>
<p>
This exploration shows the kind of information in AidData’s <a href="http://aiddata.org/data/chinese-global-official-finance-dataset">“Chinese Global Official Finance”</a> dataset. While offering only a partial, unofficial look at the country’s bilateral financial flows, it’s a detailed look at the activities of an increasingly prominent donor.</p>
</div>
</div>
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</script>Wed, 18 Oct 2017 11:00:00 -0400Tariq KhokharChart: An Over 30-Fold Increase in Turkey's Power Generation Capacityhttp://blogs.worldbank.org/opendata/chart-over-30-fold-increase-turkeys-power-generation-capacity
<iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="450" id="datawrapper-chart-S5gJ8" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//datawrapper.dwcdn.net/S5gJ8/4/" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["S5gJ8"]={},window.datawrapper["S5gJ8"].embedDeltas={"100":696,"200":543,"300":518,"400":475,"500":475,"600":475,"700":450,"800":450,"900":450,"1000":450},window.datawrapper["S5gJ8"].iframe=document.getElementById("datawrapper-chart-S5gJ8"),window.datawrapper["S5gJ8"].iframe.style.height=window.datawrapper["S5gJ8"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["S5gJ8"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof a.data["datawrapper-height"])for(var b in a.data["datawrapper-height"])if("S5gJ8"==b)window.datawrapper["S5gJ8"].iframe.style.height=a.data["datawrapper-height"][b]+"px"});</script>
<p>
Since 1970, the electricity generation capacity of Turkey has increased more than 30-fold to reach 70,000 MW in March 2015. In a country of nearly 80 million people, demand for electricity has risen about 7 percent annually in recent years, requiring steady efforts to expand the sources of reliable and clean power. Starting in the early 2000s, through a series of interlinked measures supported by the World Bank Group, the country has worked to meet this growing demand, while spurring private-sector investment and innovation. <a href="http://www.worldbank.org/en/news/immersive-story/2017/09/26/powering-transformation-the-world-bank-groups-commitment-to-success">Read more.</a><br />
&nbsp;</p>
<!--break-->Fri, 06 Oct 2017 13:00:00 -0400Tariq Khokhar